Using SNOMED semantic concept groupings to enhance semantic-type assignment consistency in the UMLS

Duo Wei, Michael Halper, Gai Elhanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

SNOMED concepts make up a significant percentage of the UMLS Metathesaurus. Hence, the correctness of their semantic type (ST) assignments contributes significantly to the overall correctness of ST assignments throughout the UMLS. Two kinds of semantic concept groupings within SNOMED are employed to automatically check for potentially inconsistent ST assignments, based on their collective sets of assignments. The first kind of concept grouping, called a semantic uniformity group (SUG), is based on concepts' properties and hierarchical configurations. The second kind constitutes intersections of groupings of the first kind ("overlapping SUG" (OSUG)). The methodology is applied to SNOMED's Specimen hierarchy, where 448 concepts residing in 40 SUGs are analyzed. A hypothesis concerning the fact that OSUGs can be stronger indicators of inconsistencies than SUGs is considered. The results show that our methodology can be effective in finding ST assignment problems and thus can augment the suite of techniques available for managing the enormous amount of such assignments.

Original languageEnglish (US)
Title of host publicationIHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Pages825-829
Number of pages5
DOIs
StatePublished - Mar 8 2012
Event2nd ACM SIGHIT International Health Informatics Symposium, IHI'12 - Miami, FL, United States
Duration: Jan 28 2012Jan 30 2012

Publication series

NameIHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium

Other

Other2nd ACM SIGHIT International Health Informatics Symposium, IHI'12
Country/TerritoryUnited States
CityMiami, FL
Period1/28/121/30/12

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Health Information Management

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